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Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation

Osteosarcoma is the most common primary malignant tumor of bone. Tumorigenic investigation of osteosarcoma cell lines may facilitate preclinical studies of targeted therapy. Therefore, the aim of this study was to explore the tumorigenicity-associated genes in osteosarcoma cells. We found that 138 g...

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Autores principales: Jiang, Shaojie, Zhou, Fei, Zhang, Yanhua, Zhou, Weiping, Zhu, Linghua, Zhang, Miaofeng, Luo, Jingfeng, Ma, Rui, Xu, Xiufang, Zhu, Jiying, Dong, Xue, Zhang, Shuangling, Fang, Jie, Sun, Jihong, Yang, Xiaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7150450/
https://www.ncbi.nlm.nih.gov/pubmed/32284759
http://dx.doi.org/10.7150/jca.37393
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author Jiang, Shaojie
Zhou, Fei
Zhang, Yanhua
Zhou, Weiping
Zhu, Linghua
Zhang, Miaofeng
Luo, Jingfeng
Ma, Rui
Xu, Xiufang
Zhu, Jiying
Dong, Xue
Zhang, Shuangling
Fang, Jie
Sun, Jihong
Yang, Xiaoming
author_facet Jiang, Shaojie
Zhou, Fei
Zhang, Yanhua
Zhou, Weiping
Zhu, Linghua
Zhang, Miaofeng
Luo, Jingfeng
Ma, Rui
Xu, Xiufang
Zhu, Jiying
Dong, Xue
Zhang, Shuangling
Fang, Jie
Sun, Jihong
Yang, Xiaoming
author_sort Jiang, Shaojie
collection PubMed
description Osteosarcoma is the most common primary malignant tumor of bone. Tumorigenic investigation of osteosarcoma cell lines may facilitate preclinical studies of targeted therapy. Therefore, the aim of this study was to explore the tumorigenicity-associated genes in osteosarcoma cells. We found that 138 genes were highly expressed and 86 genes were lowly expressed in highly tumorigenic osteosarcoma cell lines (143B, MNNG/HOS, and SJSA-1) compared with poorly tumorigenic osteosarcoma cell lines (MG-63, Saos-2, and U-2 OS). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that highly expressed genes were associated with amino acids and energy metabolism, while lowly expressed genes were associated with cell cycle and DNA replication. Gene Ontology (GO) analysis showed that highly expressed genes were associated with endoplasmic reticulum stress response and aggrephagy, whereas lowly expressed genes were correlated with extracellular matrix assembly and DNA damage response. Further analysis identified six highly expressed genes and six lowly expressed genes. Three of highly expressed genes (DDX10, FOXA2, and HEY1) were correlated with poor prognosis, while three of lowly expressed genes (CYP26B1, GP1BB, and IFI44) showed the opposite trend in patients with osteosarcoma. Knockdown of HEY1 significantly inhibited the tumorigenicity of 143B cells in BALB/c nude mice.
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spelling pubmed-71504502020-04-13 Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation Jiang, Shaojie Zhou, Fei Zhang, Yanhua Zhou, Weiping Zhu, Linghua Zhang, Miaofeng Luo, Jingfeng Ma, Rui Xu, Xiufang Zhu, Jiying Dong, Xue Zhang, Shuangling Fang, Jie Sun, Jihong Yang, Xiaoming J Cancer Research Paper Osteosarcoma is the most common primary malignant tumor of bone. Tumorigenic investigation of osteosarcoma cell lines may facilitate preclinical studies of targeted therapy. Therefore, the aim of this study was to explore the tumorigenicity-associated genes in osteosarcoma cells. We found that 138 genes were highly expressed and 86 genes were lowly expressed in highly tumorigenic osteosarcoma cell lines (143B, MNNG/HOS, and SJSA-1) compared with poorly tumorigenic osteosarcoma cell lines (MG-63, Saos-2, and U-2 OS). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that highly expressed genes were associated with amino acids and energy metabolism, while lowly expressed genes were associated with cell cycle and DNA replication. Gene Ontology (GO) analysis showed that highly expressed genes were associated with endoplasmic reticulum stress response and aggrephagy, whereas lowly expressed genes were correlated with extracellular matrix assembly and DNA damage response. Further analysis identified six highly expressed genes and six lowly expressed genes. Three of highly expressed genes (DDX10, FOXA2, and HEY1) were correlated with poor prognosis, while three of lowly expressed genes (CYP26B1, GP1BB, and IFI44) showed the opposite trend in patients with osteosarcoma. Knockdown of HEY1 significantly inhibited the tumorigenicity of 143B cells in BALB/c nude mice. Ivyspring International Publisher 2020-03-26 /pmc/articles/PMC7150450/ /pubmed/32284759 http://dx.doi.org/10.7150/jca.37393 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Jiang, Shaojie
Zhou, Fei
Zhang, Yanhua
Zhou, Weiping
Zhu, Linghua
Zhang, Miaofeng
Luo, Jingfeng
Ma, Rui
Xu, Xiufang
Zhu, Jiying
Dong, Xue
Zhang, Shuangling
Fang, Jie
Sun, Jihong
Yang, Xiaoming
Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation
title Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation
title_full Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation
title_fullStr Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation
title_full_unstemmed Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation
title_short Identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation
title_sort identification of tumorigenicity-associated genes in osteosarcoma cell lines based on bioinformatic analysis and experimental validation
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7150450/
https://www.ncbi.nlm.nih.gov/pubmed/32284759
http://dx.doi.org/10.7150/jca.37393
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